2. Determine the definition of the piece wise linear function shown in each of the graphs
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
2. Determine the definition of the
3. Consider the following sets of data points. Decide in which cases you would chose a piecewise linear model to fit the data points.
4. For any part of question 3 that was suitable for meddling with piecewise linear function: a) draw this model “by eye” b) estimate the value of y when x=12
6. Consider the set of data points in the table
![3 Consider ihe following seis of data points.
Decide in which cases you would choose
a piecewise linear model to fit the data
poinis.
2 Determine the definition of the piecewise
linear function shown in each of the graphs.
5.
20
4.
3-
20
18
2-
12
-4
-3
-2 -1
2 3 4
4. 12 16 20 24 28 32 36
-4SNS...
16
くxく3
14
12
10-
4-
21
9 10 it 12 13 14
3
2
14
12
10
43
-2
-1
3
4.
6-
...<xS2
Stx) =
...<N$4](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F88b97325-0841-4276-a045-4365da698e88%2Ff738012e-721b-4642-9ec5-fafaf6cece01%2F8kv7ilg_processed.jpeg&w=3840&q=75)
![4 Fur any part of question3 that was suinable
for modelling with a piecewise lincar function:
Draw this model "by eye".
b Estimate the value of y wvhen x= 12.
5 Consider the set of data points in the table.
46
9 10.5 12 13 15 14 17 16 18
y 53 48 4 4.2 3.4 3.1
3.
247.3 B 11S 11 15
a Plot these points on a scatter diagram.
b Find a piccewise linear model that best
lits these data points.
C Draw your niodel on the same set of
axes used for pari a.
d Hence estimate the value of y when:
i x= 8
il x 15.5](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F88b97325-0841-4276-a045-4365da698e88%2Ff738012e-721b-4642-9ec5-fafaf6cece01%2F7poywwg_processed.jpeg&w=3840&q=75)
![](/static/compass_v2/shared-icons/check-mark.png)
Step by step
Solved in 4 steps with 1 images
![Blurred answer](/static/compass_v2/solution-images/blurred-answer.jpg)
![Advanced Engineering Mathematics](https://www.bartleby.com/isbn_cover_images/9780470458365/9780470458365_smallCoverImage.gif)
![Numerical Methods for Engineers](https://www.bartleby.com/isbn_cover_images/9780073397924/9780073397924_smallCoverImage.gif)
![Introductory Mathematics for Engineering Applicat…](https://www.bartleby.com/isbn_cover_images/9781118141809/9781118141809_smallCoverImage.gif)
![Advanced Engineering Mathematics](https://www.bartleby.com/isbn_cover_images/9780470458365/9780470458365_smallCoverImage.gif)
![Numerical Methods for Engineers](https://www.bartleby.com/isbn_cover_images/9780073397924/9780073397924_smallCoverImage.gif)
![Introductory Mathematics for Engineering Applicat…](https://www.bartleby.com/isbn_cover_images/9781118141809/9781118141809_smallCoverImage.gif)
![Mathematics For Machine Technology](https://www.bartleby.com/isbn_cover_images/9781337798310/9781337798310_smallCoverImage.jpg)
![Basic Technical Mathematics](https://www.bartleby.com/isbn_cover_images/9780134437705/9780134437705_smallCoverImage.gif)
![Topology](https://www.bartleby.com/isbn_cover_images/9780134689517/9780134689517_smallCoverImage.gif)